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The Scientific World Journal
Volume 2014, Article ID 145807, 10 pages
http://dx.doi.org/10.1155/2014/145807
Research Article

Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification

1College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, China
2School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China

Received 3 October 2013; Accepted 30 December 2013; Published 12 February 2014

Academic Editors: Y. Lei and M. Riera-Guasp

Copyright © 2014 Pengfei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Mien Van, and Hee-Jun Kang, “Bearing-fault diagnosis using non-local means algorithm and empirical mode decomposition-based feature extraction and two-stage feature selection,” Iet Science Measurement & Technology, vol. 9, no. 6, pp. 671–680, 2015. View at Publisher · View at Google Scholar
  • Veerappa B. Pagi, Ramesh S. Wadawadagi, and Basavaraj S. Anami, “Fault localization in motorcycles using wavelet packet energy distribution,” Proceedings of the IEEE International Conference on Soft-Computing and Network Security, ICSNS 2015, 2015. View at Publisher · View at Google Scholar
  • Bingzhen Jiang, Jiawei Xiang, and Yanxue Wang, “Rolling bearing fault diagnosis approach using probabilistic principal component analysis denoising and cyclic bispectrum,” Journal Of Vibration And Control, vol. 22, no. 10, pp. 2420–2433, 2016. View at Publisher · View at Google Scholar
  • Jiawei Xiang, and Yongteng Zhong, “A Novel Personalized Diagnosis Methodology Using Numerical Simulation and an Intelligent Method to Detect Faults in a Shaft,” Applied Sciences, vol. 6, no. 12, pp. 414, 2016. View at Publisher · View at Google Scholar
  • Qing Xiong, Weihua Zhang, Tianwei Lu, Guiming Mei, and Shulin Liang, “A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution,” Shock and Vibration, vol. 2016, pp. 1–12, 2016. View at Publisher · View at Google Scholar
  • Jiawei Xiang, and Yongteng Zhong, “A fault detection strategy using the enhancement ensemble empirical mode decomposition and random decrement technique,” Microelectronics Reliability, vol. 75, pp. 317–326, 2017. View at Publisher · View at Google Scholar
  • Jiawei Xiang, and Yongteng Zhong, “A new fault detection strategy using the enhancement ensemble empirical mode decomposition,” Journal of Physics: Conference Series, vol. 842, no. 1, 2017. View at Publisher · View at Google Scholar